Can we use the bacteria in our gut to measure how biologically old we are? Some researchers certainly think we can and have developed a microbiome clock that examines the bacteria living in our guts to predict our age.
The gut microbiome is a complex and ever-changing ecosystem populated by a myriad of archaea, eukarya, viruses, and bacteria. Four microbial phyla, Firmicutes, Bacteroides, Proteobacteria, and Actinobacteria, make up 98% of the total population of the intestinal microbiome.
The microbiome is a complex ecosystem that regulates various aspects of gut function along with the immune system, the nutrient supply, and metabolism. It also helps to control the growth of pathogenic bacteria, protects from invasive microorganisms, and maintains the intestinal barrier.
It is well documented that the gut microbiome experiences considerable changes during the aging process with the diversity and number of beneficial bacteria declining, which typically accompanies an increase of harmful bacteria. These detrimental changes are thought by some researchers to be the origin point of inflammaging, the chronic systemic inflammation typically seen in older people that impairs healthy tissue repair and supports the development of a number of age-related diseases.
The gut microbiome is a highly complex ecosystem and can be influenced not only by aging but also by diet, lifestyle, smoking, exercise, alcohol consumption, and environmental conditions. Additionally, everyone has significantly different microbiomes with regional and even ethnic differences being present. This has made past attempts at creating a microbiome clock to ascertain a person’s biological age a challenge.
Building a microbiome aging clock
Researchers from the laboratory of Dr. Vadim Gladyshev at Harvard Medical School and Insilico Medicine joined forces for a new study, which analyzed the data from 13 studies on the human gut microbiome and aggregated it to see if developing an aging biomarker clock based on the microbiome was plausible .
The team trained a deep neural network using over 1000 microflora samples, and the resulting clock predicted the age of the person with a mean margin of error of 5.9 to 6.8 years.
The findings support the idea that the microbiome does change in a somewhat predictable manner in the context of aging and that it may be possible to refine the clock further for much higher accuracy. The researchers’ next step will be to focus on specific populations of bacteria to see which ones have an influence over the rate at which we age. This should allow microbiome clocks of increasing accuracy to be developed.
The human gut microbiome is a complex ecosystem that both affects and is affected by its host status. Previous metagenomic analyses of gut microflora revealed associations between specific microbes and host age. Nonetheless there was no reliable way to tell a host’s age based on the gut community composition. Here we developed a method of predicting hosts’ age based on microflora taxonomic profiles using a cross-study dataset and deep learning. Our best model has an architecture of a deep neural network that achieves the mean absolute error of 5.91 years when tested on external data. We further advance a procedure for inferring the role of particular microbes during human aging and defining them as potential aging biomarkers. The described intestinal clock represents a unique quantitative model of gut microflora aging and provides a starting point for building host aging and gut community succession into a single narrative.
This represents a good first attempt at creating a microbiome aging clock, and subsequent refinement may allow the creation of a more accurate clock able to predict a person’s age within a lower margin of error.
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 Galkin, F., Mamoshina, P., Aliper, A., Putin, E., Moskalev, V., Gladyshev, V. N., & Zhavoronkov, A. (2020). Human gut microbiome aging clock based on taxonomic profiling and deep learning. iScience, 101199.